Paper: Detecting Compositionality of Multi-Word Expressions using Nearest Neighbours in Vector Space Models

ACL ID D13-1147
Title Detecting Compositionality of Multi-Word Expressions using Nearest Neighbours in Vector Space Models
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

We present a novel unsupervised approach to detecting the compositionality of multi-word expressions. We compute the compositional- ity of a phrase through substituting the con- stituent words with their ?neighbours? in a se- mantic vector space and averaging over the distance between the original phrase and the substituted neighbour phrases. Several meth- ods of obtaining neighbours are presented. The results are compared to existing super- vised results and achieve state-of-the-art per- formance on a verb-object dataset of human compositionality ratings.